Control of Joint Spacing During Fin Development and Regeneration
The zebrafish (Danio rerio) has emerged as a model to study vertebrate development due to rapid ontogenetic processes with external embryonic development. It is also an excellent model to study the mechanisms of regeneration and in this respect, the caudal fin is particularly convenient because it i...
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| Language: | en |
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Université d'Ottawa / University of Ottawa
2015
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| Online Access: | http://hdl.handle.net/10393/32574 http://dx.doi.org/10.20381/ruor-4237 |
| Summary: | The zebrafish (Danio rerio) has emerged as a model to study vertebrate development due to rapid ontogenetic processes with external embryonic development. It is also an excellent model to study the mechanisms of regeneration and in this respect, the caudal fin is particularly convenient because it is easily accessible for experimental manipulation. Collection of quantitative data and postulation of theoretical models have become an attractive practice to explain complex biological problems. These models are used to test hypothetical mechanisms and predict results, but they also require calibration and validation with analysis of experimental data. This thesis aims at studying the developmental control of fin joint formation, which determines segment patterns of the rays in the caudal fin of zebrafish, before and after an amputation event, through a computational approach and imaging morpho-dynamics. We used a computational approach based on a quantitative framework developed for the analysis of fish fin development and regeneration and more specifically focused our analysis on the pattern of bone segments forming the ray. This allowed us to generate visual maps of the developing and regenerating caudal fins based on average fin data. The results from our experimental set show that bone segments at the amputation plane are longer after regeneration than segments at the same position in non-amputated fins. We also optimized a previously proposed morphogen driven model for fin growth and regeneration to accurately recreate segment numbers based on experimental data. Finally, we collected segment regression data that could be integrated into a new visual map method to analyse fin bony segment patterns. |
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